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Shengli Sun
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Time-Weighted Uncertain Nearest Neighbor Collaborative Filtering Algorithm Zhigao Zheng; Jing Liu; Ping Wang; Shengli Sun
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 8: August 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i8.pp6393-6402

Abstract

To overcome the limitations of the traditional collaborative filtering recommendation algorithm, this paper proposed a Time-Weighted Uncertain Nearest Neighbor Collaborative Filtering Algorithm (TWUNCF). According to the actual application situation of recommendation system, the author weighted the product similarity and user similarity to ensure the data validity firstly, and then calculate the similarities of user and product and choose the trusted neighbor group as the recommended object adaptively based on the weight. Experimental results show that the algorithm can be used to improve data validity according to the time attribute, and balance the impact the different groups on the recommendation result, and avoid the problems which caused by the data sparseness. Theoretical analysis and experimental demonstrations show that the algorithm this paper proposed outperforms existing algorithms in recommendation quality, and improve the system's accuracy and recommendation efficiency.
Co-Authors Jing Liu Ping Wang Zhigao Zheng